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Quantum Monte Carlo Approaches for Correlated Systems
Over the past several decades, computational approaches to studying strongly-interacting systems have become increasingly varied and sophisticated. This book provides a comprehensive introduction to state-of-the-art quantum Monte Carlo techniques relevant for applications in correlated systems. Providing a clear overview of variational wave functions, and featuring a detailed presentation of stochastic samplings including Markov chains and Langevin dynamics, which are developed into a discussion of Monte Carlo methods. The variational technique is described, from foundations to a detailed description of its algorithms. Further topics discussed include optimisation techniques, real-time dynamics and projection methods, including Green's function, reptation and auxiliary-field Monte Carlo, from basic definitions to advanced algorithms for efficient codes, and the book concludes with recent developments on the continuum space. Quantum Monte Carlo Approaches for Correlated Systems provides an extensive reference for students and researchers working in condensed matter theory or those interested in advanced numerical methods for electronic simulation.
Introduction to Frustrated Magnetism
The field of highly frustrated magnetism has developed considerably and expanded over the last 15 years. Issuing from canonical geometric frustration of interactions, it now extends over other aspects with many degrees of freedom such as magneto-elastic couplings, orbital degrees of freedom, dilution effects, and electron doping. Its is thus shown here that the concept of frustration impacts on many other fields in physics than magnetism. This book represents a state-of-the-art review aimed at a broad audience with tutorial chapters and more topical ones, encompassing solid-state chemistry, experimental and theoretical physics.
Effective Models for Low-Dimensional Strongly Correlated Systems
These proceedings cover the most recent developments in the fields of high temperature superconductivity, magnetic materials and cold atoms in traps. Special emphasis is given to recently developed numerical and analytical methods, such as effective model Hamiltonians, density matrix renormalization group as well as quantum Monte Carlo simulations. Several of the contributions are written by the pioneers of these methods.
Intruders
A tense, twisting, international thriller. Deftly written and engrossing, E. C. Scullion's debut Intruders, quickly drew me in, and the intrigue and pace kept me turning pages. A talented writer to watch' Adam HamdyThere is a safe, in a house, inside a secure compound in South America. Your job - the job of your team - is to bring me the contents of that safe.Disgraced security consultant Tom Holt accepts a job from a mysterious lawyer, on behalf of a client named Capricorn. Holt's team comprises Anil, a safe-cracking ex-con; Ray, a disgruntled logistics man, and Becca, a fiery red-headed thief with as much attitude as she has talent for picking pockets.On arrival in the alluring Argentine city of Buenos Aires, Holt's past swiftly catches up with him. As he begins to question the client's motives, he finds there are darker, more sinister characters who show loyalty to his employer. Who is Capricorn? What's inside the safe? Tom Holt is about to discover how far he will go to expose the truth, even if it means risking everything, including his own life.
Measurement and Modeling of Polychlorinated Biphenyl Availability from Contaminated Sediment and Evaluation of Ecosystem Recovery
This research comprises measurement and modeling of polychlorinated biphenyl (PCB) bioaccumulation from contaminated sediments and the evaluation of an in-situ sorbent amendment with activated carbon (AC) to allow ecosystem recovery. Laboratory bioassays with the deposit feeding polychaete Neanthes arenaceodentata, showed that PCB uptake from the aqueous phase accounted for less than three percent of the total uptake. High sediment ingestion rates and fast bioaccumulation of PCBs exceeding sediment concentration within 14 days of exposure suggest that deposit feeders are promising test organisms to evaluate local sediment conditions. A biodynamic model that described bioaccumulation by a mas...
Mathematical Aspects of Deep Learning
In recent years the development of new classification and regression algorithms based on deep learning has led to a revolution in the fields of artificial intelligence, machine learning, and data analysis. The development of a theoretical foundation to guarantee the success of these algorithms constitutes one of the most active and exciting research topics in applied mathematics. This book presents the current mathematical understanding of deep learning methods from the point of view of the leading experts in the field. It serves both as a starting point for researchers and graduate students in computer science, mathematics, and statistics trying to get into the field and as an invaluable reference for future research.
Numerical Analysis meets Machine Learning
Numerical Analysis Meets Machine Learning series, highlights new advances in the field, with this new volume presenting interesting chapters. Each chapter is written by an international board of authors. - Provides the authority and expertise of leading contributors from an international board of authors - Presents the latest release in the Handbook of Numerical Analysis series - Updated release includes the latest information on the Numerical Analysis Meets Machine Learning
Field-Theoretic Simulations in Soft Matter and Quantum Fluids
This monograph provides an introduction to field-theoretic simulations in classical soft matter and Bose quantum fluids. The method represents a new class of molecular computer simulation in which continuous fields, rather than particle coordinates, are sampled and evolved. Field-theoretic simulations are capable of analysing the properties of systems that are challenging for traditional simulation techniques, including dense phases of high molecular weight polymers, self-assembling fluids, and quantum fluids at finite temperature. The monograph details analytical methods for converting classical and quantum many-body problems to equilibrium field theory models with a molecular basis. Numerical methods are described that enable efficient, accurate, and scalable simulations of such models on modern computer hardware, including graphics processing units (GPUs). Extensions to non-equilibrium systems are discussed, along with an introduction to advanced field-theoretic simulation techniques including free energy estimation, alternative ensembles, coarse-graining, and variable cell methods.
Topological Phases of Matter
This important graduate level text unites the physical mechanisms behind the phenomena of topological matter within a theoretical framework.
